As humans interact more often and more intimately with computers, and as computational systems become an ever more important element of our society, playing roles in education, the production of culture and goods, and management, it is inevitable that we should seek to interact with these systems in ways that take advantage of our powerful emotional capabilities. Creating Synthetic Emotions through Technological and Robotic Advancements compiles progressive research in the emerging and groundbreaking fields of artificial emotions, affective computing, and sociable robotics that allow humans to begin the once impossible-seeming task of interacting with robots, systems, devices, and agents. This landmark volume brings together expert international researchers to expound upon these topics as synthetic emotions move toward becoming a daily reality.

Agenda Relevance is the first volume in the authors' omnibus investigation of
the logic of practical reasoning, under the collective title, A Practical Logic
of Cognitive Systems. In this highly original approach, practical reasoning is
identified as reasoning performed with comparatively few cognitive assets,
including resources such as information, time and computational capacity. Unlike
what is proposed in optimization models of human cognition, a practical reasoner
lacks perfect information, boundless time and unconstrained access to
computational complexity. The practical reasoner is therefore obliged to be a
cognitive economizer and to achieve his cognitive ends with considerable
efficiency. Accordingly, the practical reasoner avails himself of various
scarce-resource compensation strategies. He also possesses neurocognitive
traits that abet him in his reasoning tasks. Prominent among these is the
practical agent's striking (though not perfect) adeptness at evading irrelevant
information and staying on task. On the approach taken here, irrelevancies are
impediments to the attainment of cognitive ends. Thus, in its most basic sense,
relevant information is cognitively helpful information. Information can then be
said to be relevant for a practical reasoner to the extent that it advances or
closes some cognitive agenda of his. The book explores this idea with a
conceptual detail and nuance not seen the standard semantic, probabilistic and
pragmatic approaches to relevance; but wherever possible, the authors seek to
integrate alternative conceptions rather than reject them outright. A further
attraction of the agenda-relevance approach is the extent to which its principal
conceptual findings lend themselves to technically sophisticated re-expression
in formal models that marshal the resources of time and action logics and
label led deductive systems.

Agenda Relevance is necessary reading for researchers in logic, belief
dynamics, computer science, AI, psychology and neuroscience, linguistics,
argumentation theory, and legal reasoning and forensic science, and will repay
study by graduate students and senior undergraduates in these same fields.

Key features:

relevance
action and agendas
practical reasoning
belief dynamics
non-classical logics
labelled deductive systems

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Research on living systems, human level artificial systems, and machines that exhibit intelligent behavioral characteristics is fundamental in order to tackle complex and dynamic issues in nature and create applicable solutions. Investigations into Living Systems, Artificial Life, and Real-World Solutions provides original research on the theoretical and applied aspects of artificial life, as well as addresses scientific, psychological, and social issues of synthetic life-like behavior and abilities. This book is essential for researchers, students, and scientists interested in the emerging discipline of artificial life to further understand and solve real-world problems.

Tech visionary and co-founder of Manas AI Reid Hoffman shares his unique insider’s perspective on an AI-powered future, making the case for its potential to unlock a world of possibilities.

Superagency offers a roadmap for using AI inclusively and adaptively to improve our lives and create positive change. While acknowledging challenges like disinformation and potential job changes, the book focuses on AI’s immense potential to increase individual agency and create better outcomes for society as a whole.

Imagine AI tutors personalizing education for each child, researchers rapidly discovering cures for diseases like Alzheimer's and cancer, and AI advisors empowering people to navigate complex systems and achieve their goals. Hoffman and co-author, tech and culture writer Greg Beato envision a world where these possibilities, and many more, become a reality.

Superagency challenges conventional fears, inviting us to view the future through a lens of opportunity, rather than fear. It’s a call to action – to embrace AI with excitement and actively shape a world where human ingenuity and the power of AI combine to create something extraordinary.

Entrepreneur Reid Hoffman is a co-founder of LinkedIn, Inflection AI, and Manas AI. He is also host of the podcasts Possible and Masters of Scale.

The natural social behavior of large groups of animals, such as flocks of birds, schools of fish, or colonies of ants has fascinated scientists for hundreds of years, if not longer, due to the intricate nature of their interactions and their ability to move and work together seemingly effortlessly. Innovations and Developments of Swarm Intelligence Applications explores the emerging realm of swarm intelligence, which finds its basis in the natural social behavior of animals. The study and application of this swarm behavior has led scientists to a new world of research as ways are found to apply this behavior to independent intelligent agents, creating complex solutions for real world applications. Worldwide contributions have been seamlessly combined in this comprehensive reference, providing a wealth of new information for researchers, academicians, students, and engineers.

In recent years, the need for smart equipment has increased exponentially with the upsurge in technological advances. To work to their fullest capacity, these devices need to be able to communicate with other devices in their network to exchange information and receive instructions. Computational Intelligence in the Internet of Things is an essential reference source that provides relevant theoretical frameworks and the latest empirical research findings in the area of computational intelligence and the Internet of Things. Featuring research on topics such as data analytics, machine learning, and neural networks, this book is ideally designed for IT specialists, managers, professionals, researchers, and academicians.

This volume provides an extensive overview of the Ethics of Artificial Intelligence for the Sustainable Development Goals. The authors are experts contributing with perspectives from different fields. The comprehensive collection of chapters illustrates the pressing governance problems related to using AI for the SDGs, and case studies describing how AI is advancing and can advance the achievement of the Goals. Students, scholars, and practitioners working on AI for SDGs, the ethical governance of AI, sustainability, and the fourth revolution can find this book a helpful reference.

The advent of the World Wide Web has sparked renewed interest in the area of intelligent information technologies. There is a growing interest in developing intelligent technologies that allow users to accomplish complex tasks in Web-centric environments with relative ease, utilizing such technologies as intelligent agents, distributed computing in heterogeneous environments, and computer supported collaborative work. Intelligent, Adaptive and Reasoning Technologies: New Developments and Applications is a comprehensive collection of work from researchers in related fields such as information systems, distributed AI, intelligent agents, and collaborative work that explores and discusses various aspects of design and development of intelligent technologies. This book provides a forum for academics and practitioners to explore research issues related to not only the design, implementation and deployment of intelligent systems and technologies, but also economic issues and organizational impact.

Edge computing is focused on devices and technologies that are attached to the internet of things (IoT). Identifying IoT use across a range of industries and measuring strategic values helps identify what technologies to pursue and can avoid wasted resources on deployments with limited values. The Handbook of Research on Edge Computing and Computational Intelligence Paradigms for the IoT is a critical research book that provides a complete insight on the recent advancements and integration of intelligence in IoT. This book highlights various topics such as disaster prediction, governance, and healthcare. It is an excellent resource for researchers, working professionals, academicians, policymakers, and defense companies.

Immersive technology as an umbrella concept consists of multiple emerging technologies including augmented reality (AR), virtual reality (VR), gaming, simulation, and 3D printing. Research has shown immersive technology provides unique learning opportunities for experiential learning, multiple perspectives, and knowledge transfer. Due to its role in influencing learners' cognitive and affective processes, it is shown to have great potential in changing the educational landscape in the decades to come. However, there is a lack of general cognitive and affective theoretical framework to guide the diverse aspects of immersive technology research. In fact, lacking the cognitive and affective theoretical framework has begun to hamper the design and application of immersive technology in schools and related professional training. Cognitive and Affective Perspectives on Immersive Technology in Education is an essential research book that explores methods and implications for the design and implementation of upcoming immersive technologies in pedagogical and professional development settings. The book includes case studies that highlight the cognitive and affective processes in immersive technology as well as the successful applications of immersive technology in education. Featuring a wide range of topics such as curriculum design, K-12 education, and mobile learning, this book is ideal for academicians, educators, policymakers, curriculum developers, instructional designers, administrators, researchers, and students.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us-and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem. Systems cull resumes until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole-and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands. The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called "artificial intelligence." They are steadily replacing both human judgment and explicitly programmed software. In best-selling author Brian Christian's riveting account, we meet the alignment problem's "first-responders," and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they-and we-succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity's biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture-and finds a story by turns harrowing and hopeful.

This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and from the standpoint of application for software implementation in neuroscience research. These include those both commonly used (traditional established) and state of the art methods. The former is easier to do due to the availability of appropriate software. To understand the methods it is necessary to have some mathematical knowledge which is explained in the book with the help of figures and descriptions of the theory behind the software. In addition, the book includes numerical examples to guide readers on the working of existing popular software. The use of mathematics is reduced and simplified for non-experts using established methods, which also helps in avoiding mistakes in application and interpretation. Finally, the book enables the reader to understand and conceptualize the overall flow of brain imaging data analysis, particularly for statisticians and data-scientists unfamiliar with this area. The state of the art method described in the book has a multivariate approach developed by the authors' team. Since brain imaging data, generally, has a highly correlated and complex structure with large amounts of data, categorized into big data, the multivariate approach can be used as dimension reduction by following the application of statistical methods. The R package for most of the methods described is provided in the book. Understanding the background theory is helpful in implementing the software for original and creative applications and for an unbiased interpretation of the output. The book also explains new methods in a conceptual manner. These methodologies and packages are commonly applied in life science data analysis. Advanced methods to obtain novel insights are introduced, thereby encouraging the development of new methods and applications for research into medicine as a neuroscience.

Emotions convey significant information through means of natural language analysis, embodiment, and emotional signing. Machines equipped with the ability to experience and interpret emotions perform better in complex environments and share in the emotionally-rich social context. The Handbook of Research on Synthesizing Human Emotion in Intelligent Systems and Robotics presents a solid framework for taking human-robot interaction closer to its full potential. Presenting a close look at all the factors involved in modeling emotions and applying a thorough understanding of human emotional recognition to technology, this volume appeals to active researchers in the fields of artificial emotions, artificial intelligence, computing, robotics, philosophy, and psychology, as well as to students interested in the research of synthetic emotions.

This Book is comprised of solutions for the treatment of cognitive diseases with Bionics or Bioinspired Algorithms using future technologies such as artificial intelligence, machine learning, Internet of Things (IoT), data science, and more. Studying the behavior of nature and providing the medical engineering solutions would not only be unique but would result in substantial contribution in solution of so many cognitive disease problems which are not detected correctly in initial stages. This publication would be a breakthrough in the field of medical science, especially in the field of cognitive diseases by providing solutions in the form of algorithms and devices that could be useful for the brain disease patient for early detection. This book is essential for various medical research centers, engineering institutions across the world, medical colleges, biomedical research centers, and electronics and communication research centers.

Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.

The body of research in all aspects of Semantic Web development, design, and application continues to grow alongside new trends in the information systems community. Semantic-Enabled Advancements on the Web: Applications Across Industries reviews current and future trends in Semantic Web research with the aim of making existing and potential applications more accessible to a broader community of academics, practitioners, and industry professionals. Covering topics including recommendation systems, semantic search, and ontologies, this reference is a valuable contribution to the existing literature in this discipline.